Merge pull request #9 from jond01/chore/modernize/black

Format all the code base with `black`

medio/__init__.py

@@ -3,6 +3,6 @@
 from medio.read_save import read_img, save_img, save_dir
 from medio import backends, metadata, medimg, utils
 
-__version__ = '0.4.1'
+__version__ = "0.4.1"
 
-__all__ = ['read_img', 'save_img', 'save_dir', 'MetaData', 'Affine', '__version__']
+__all__ = ["read_img", "save_img", "save_dir", "MetaData", "Affine", "__version__"]

medio/backends/nib_io.py

@@ -8,14 +8,11 @@
 
 
 class NibIO:
- coord_sys = 'nib'
- RGB_DTYPE = np.dtype([('R', np.uint8),
- ('G', np.uint8),
- ('B', np.uint8)])
- RGBA_DTYPE = np.dtype([('R', np.uint8),
- ('G', np.uint8),
- ('B', np.uint8),
- ('A', np.uint8)])
+ coord_sys = "nib"
+ RGB_DTYPE = np.dtype([("R", np.uint8), ("G", np.uint8), ("B", np.uint8)])
+ RGBA_DTYPE = np.dtype(
+ [("R", np.uint8), ("G", np.uint8), ("B", np.uint8), ("A", np.uint8)]
+ )
 
  @staticmethod
  def read_img(input_path, desired_axcodes=None, header=False, channels_axis=None):
@@ -28,16 +25,20 @@ def read_img(input_path, desired_axcodes=None, header=False, channels_axis=None)
  :return: image array and corresponding metadata
  """
  img_struct = nib.load(input_path)
- orig_ornt_str = ''.join(nib.aff2axcodes(img_struct.affine))
+ orig_ornt_str = "".join(nib.aff2axcodes(img_struct.affine))
  if desired_axcodes is not None:
  img_struct = NibIO.reorient(img_struct, desired_axcodes)
  img = np.asanyarray(img_struct.dataobj)
  if channels_axis is not None:
  img = NibIO.unravel_array(img, channels_axis)
  affine = Affine(img_struct.affine)
- metadata = MetaData(affine=affine, orig_ornt=orig_ornt_str, coord_sys=NibIO.coord_sys)
+ metadata = MetaData(
+ affine=affine, orig_ornt=orig_ornt_str, coord_sys=NibIO.coord_sys
+ )
  if header:
- metadata.header = {key: img_struct.header[key] for key in img_struct.header.keys()}
+ metadata.header = {
+ key: img_struct.header[key] for key in img_struct.header.keys()
+ }
  return img, metadata
 
  @staticmethod
@@ -79,30 +80,34 @@ def unravel_array(array, channels_axis=-1):
  np.dtype([('R', 'uint8'), ('G', 'uint8'), ('B', 'uint8')])
  Convert it into an array with dtype 'uint8' and 3 channels for RGB in an additional last dimension"""
  dtype = array.dtype
- if not (hasattr(dtype, '__len__') and len(dtype) > 1):
+ if not (hasattr(dtype, "__len__") and len(dtype) > 1):
  return array
  return np.stack([array[field] for field in dtype.fields], axis=channels_axis)
 
  @staticmethod
  def pack_channeled_img(img, channels_axis):
  dtype = img.dtype
  if not np.issubdtype(dtype, np.uint8):
- raise ValueError(f'RGB or RGBA images must have dtype "np.uint8", got: "{dtype}"')
+ raise ValueError(
+ f'RGB or RGBA images must have dtype "np.uint8", got: "{dtype}"'
+ )
  n_channels = img.shape[channels_axis]
  img = np.moveaxis(img, channels_axis, -1)
  r_channel = img[..., 0]
  if n_channels == 3:
  img_rgb = np.empty_like(r_channel, dtype=NibIO.RGB_DTYPE)
- img_rgb['R'] = r_channel
- img_rgb['G'] = img[..., 1]
- img_rgb['B'] = img[..., 2]
+ img_rgb["R"] = r_channel
+ img_rgb["G"] = img[..., 1]
+ img_rgb["B"] = img[..., 2]
  return img_rgb
  elif n_channels == 4:
  img_rgba = np.empty_like(r_channel, dtype=NibIO.RGBA_DTYPE)
- img_rgba['R'] = r_channel
- img_rgba['G'] = img[..., 1]
- img_rgba['B'] = img[..., 2]
- img_rgba['A'] = img[..., 3]
+ img_rgba["R"] = r_channel
+ img_rgba["G"] = img[..., 1]
+ img_rgba["B"] = img[..., 2]
+ img_rgba["A"] = img[..., 3]
  return img_rgba
  else:
- raise ValueError(f'Invalid number of channels: {n_channels}, should be 3 (RGB) or 4 (RGBA)')
+ raise ValueError(
+ f"Invalid number of channels: {n_channels}, should be 3 (RGB) or 4 (RGBA)"
+ )

medio/backends/pdcm_io.py

@@ -14,15 +14,22 @@
 
 
 class PdcmIO:
- coord_sys = 'itk'
+ coord_sys = "itk"
  # channels axes in the transposed image for pydicom and dicom-numpy. The actual axis is the first or the second
  # value of the tuple, according to the planar configuration (which is either 0 or 1)
  DEFAULT_CHANNELS_AXES_PYDICOM = (0, -1)
  DEFAULT_CHANNELS_AXES_DICOM_NUMPY = (0, 2)
 
  @staticmethod
- def read_img(input_path, desired_ornt=None, header=False, channels_axis=None, globber='*',
- allow_default_affine=False, series=None):
+ def read_img(
+ input_path,
+ desired_ornt=None,
+ header=False,
+ channels_axis=None,
+ globber="*",
+ allow_default_affine=False,
+ series=None,
+ ):
  """
  Read a dicom file or folder (series) and return the numpy array and the corresponding metadata
  :param input_path: path-like object (str or pathlib.Path) of the file or directory to read
@@ -37,21 +44,33 @@ def read_img(input_path, desired_ornt=None, header=False, channels_axis=None, gl
  :return: numpy array and metadata
  """
  input_path = Path(input_path)
- temp_channels_axis = -1 # if there are channels, they must be in the last axis for the reorientation
+ # if there are channels, they must be in the last axis for the reorientation
+ temp_channels_axis = -1
  if input_path.is_dir():
- img, metadata, channeled = PdcmIO.read_dcm_dir(input_path, header, globber,
- channels_axis=temp_channels_axis, series=series)
+ img, metadata, channeled = PdcmIO.read_dcm_dir(
+ input_path,
+ header,
+ globber,
+ channels_axis=temp_channels_axis,
+ series=series,
+ )
  else:
  img, metadata, channeled = PdcmIO.read_dcm_file(
- input_path, header, allow_default_affine=allow_default_affine, channels_axis=temp_channels_axis)
+ input_path,
+ header,
+ allow_default_affine=allow_default_affine,
+ channels_axis=temp_channels_axis,
+ )
  img, metadata = PdcmIO.reorient(img, metadata, desired_ornt)
  # move the channels after the reorientation
  if channeled and channels_axis != temp_channels_axis:
  img = np.moveaxis(img, temp_channels_axis, channels_axis)
  return img, metadata
 
  @staticmethod
- def read_dcm_file(filename, header=False, allow_default_affine=False, channels_axis=None):
+ def read_dcm_file(
+ filename, header=False, allow_default_affine=False, channels_axis=None
+ ):
  """
  Read a single dicom file.
  Return the image array, metadata, and whether it has channels
@@ -66,13 +85,19 @@ def read_dcm_file(filename, header=False, allow_default_affine=False, channels_a
  if header:
  metadata.header = {str(key): ds[key] for key in ds.keys()}
  samples_per_pixel = ds.SamplesPerPixel
- img = PdcmIO.move_channels_axis(img, samples_per_pixel=samples_per_pixel, channels_axis=channels_axis,
- planar_configuration=ds.get('PlanarConfiguration', None),
- default_axes=PdcmIO.DEFAULT_CHANNELS_AXES_PYDICOM)
+ img = PdcmIO.move_channels_axis(
+ img,
+ samples_per_pixel=samples_per_pixel,
+ channels_axis=channels_axis,
+ planar_configuration=ds.get("PlanarConfiguration", None),
+ default_axes=PdcmIO.DEFAULT_CHANNELS_AXES_PYDICOM,
+ )
  return img, metadata, samples_per_pixel > 1
 
  @staticmethod
- def read_dcm_dir(input_dir, header=False, globber='*', channels_axis=None, series=None):
+ def read_dcm_dir(
+ input_dir, header=False, globber="*", channels_axis=None, series=None
+ ):
  """
  Reads a 3D dicom image: input path can be a file or directory (DICOM series).
  Return the image array, metadata, and whether it has channels
@@ -84,15 +109,21 @@ def read_dcm_dir(input_dir, header=False, globber='*', channels_axis=None, serie
  if header:
  # TODO: add header support, something like
  # metdata.header = [{str(key): ds[key] for key in ds.keys()} for ds in slices]
- raise NotImplementedError("header=True is currently not supported for a series")
+ raise NotImplementedError(
+ "header=True is currently not supported for a series"
+ )
  samples_per_pixel = slices[0].SamplesPerPixel
- img = PdcmIO.move_channels_axis(img, samples_per_pixel=samples_per_pixel, channels_axis=channels_axis,
- planar_configuration=slices[0].get('PlanarConfiguration', None),
- default_axes=PdcmIO.DEFAULT_CHANNELS_AXES_DICOM_NUMPY)
+ img = PdcmIO.move_channels_axis(
+ img,
+ samples_per_pixel=samples_per_pixel,
+ channels_axis=channels_axis,
+ planar_configuration=slices[0].get("PlanarConfiguration", None),
+ default_axes=PdcmIO.DEFAULT_CHANNELS_AXES_DICOM_NUMPY,
+ )
  return img, metadata, samples_per_pixel > 1
 
  @staticmethod
- def extract_slices(input_dir, globber='*', series=None):
+ def extract_slices(input_dir, globber="*", series=None):
  """Extract slices from input_dir and return them sorted"""
  files = Path(input_dir).glob(globber)
  slices = [pydicom.dcmread(filename) for filename in files]
@@ -106,24 +137,31 @@ def extract_slices(input_dir, globber='*', series=None):
  series_uid = parse_series_uids(input_dir, datasets.keys(), series, globber)
  slices = datasets[series_uid]
 
- slices.sort(key=lambda ds: ds.get('InstanceNumber', 0))
+ slices.sort(key=lambda ds: ds.get("InstanceNumber", 0))
  return slices
 
  @staticmethod
  def aff2meta(affine):
  return MetaData(affine, coord_sys=PdcmIO.coord_sys)
 
  @staticmethod
- def move_channels_axis(array, samples_per_pixel, channels_axis=None, planar_configuration=None,
- default_axes=DEFAULT_CHANNELS_AXES_PYDICOM):
+ def move_channels_axis(
+ array,
+ samples_per_pixel,
+ channels_axis=None,
+ planar_configuration=None,
+ default_axes=DEFAULT_CHANNELS_AXES_PYDICOM,
+ ):
  """Move the channels axis from the original axis to the destined channels_axis"""
  if (samples_per_pixel == 1) or (channels_axis is None):
  # no rearrangement is needed
  return array
 
  # extract the original channels axis
  if planar_configuration not in [0, 1]:
- raise ValueError(f'Invalid Planar Configuration value: {planar_configuration}')
+ raise ValueError(
+ f"Invalid Planar Configuration value: {planar_configuration}"
+ )
 
  orig_axis = default_axes[planar_configuration]
  flag = True # original channels axis is assigned
@@ -138,7 +176,7 @@ def move_channels_axis(array, samples_per_pixel, channels_axis=None, planar_conf
  break
 
  if not flag:
- raise ValueError('The original channels axis was not detected')
+ raise ValueError("The original channels axis was not detected")
 
  return np.moveaxis(array, orig_axis, channels_axis)
 
@@ -160,14 +198,20 @@ def reorient(img, metadata, desired_ornt):
  reoriented_img_struct = NibIO.reorient(img_struct, desired_ornt)
 
  img = np.asanyarray(reoriented_img_struct.dataobj)
- metadata = MetaData(reoriented_img_struct.affine, orig_ornt=orig_ornt, coord_sys=NibIO.coord_sys,
- header=metadata.header)
+ metadata = MetaData(
+ reoriented_img_struct.affine,
+ orig_ornt=orig_ornt,
+ coord_sys=NibIO.coord_sys,
+ header=metadata.header,
+ )
  # convert back to pydicom convention
  metadata.convert(PdcmIO.coord_sys)
  return img, metadata
 
  @staticmethod
- def save_arr2dcm_file(output_filename, template_filename, img_arr, dtype=None, keep_rescale=False):
+ def save_arr2dcm_file(
+ output_filename, template_filename, img_arr, dtype=None, keep_rescale=False
+ ):
  """
  Writes a dicom single file image using template file, without the intensity transformation from template dataset
  unless keep_rescale is True

medio/backends/pdcm_unpack_ds.py

@@ -4,7 +4,11 @@
 import logging
 
 import numpy as np
-from dicom_numpy.combine_slices import _validate_image_orientation, _extract_cosines, _requires_rescaling
+from dicom_numpy.combine_slices import (
+ _validate_image_orientation,
+ _extract_cosines,
+ _requires_rescaling,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -81,9 +85,10 @@ def _unpack_pixel_array(dataset, rescale=None):
  rescale = _requires_rescaling(dataset)
 
  if rescale:
- voxels = voxels.astype('int16', copy=False) # TODO: it takes time! Consider view.
- slope = getattr(dataset, 'RescaleSlope', 1)
- intercept = getattr(dataset, 'RescaleIntercept', 0)
+ # TODO: it takes time! Consider view.
+ voxels = voxels.astype("int16", copy=False)
+ slope = getattr(dataset, "RescaleSlope", 1)
+ intercept = getattr(dataset, "RescaleIntercept", 0)
  if int(slope) == slope and int(intercept) == intercept:
  slope = int(slope)
  intercept = int(intercept)
@@ -103,8 +108,9 @@ def _ijk_to_patient_xyz_transform_matrix(dataset):
 
  transform[:3, 0] = row_cosine * column_spacing
  transform[:3, 1] = column_cosine * row_spacing
- transform[:3, 2] = (np.array(dataset.slice_position(-1)) - dataset.slice_position(0)
- ) / (dataset.NumberOfFrames - 1)
+ transform[:3, 2] = (
+ np.array(dataset.slice_position(-1)) - dataset.slice_position(0)
+ ) / (dataset.NumberOfFrames - 1)
  # transform[:3, 2] = slice_cosine * slice_spacing
 
  transform[:3, 3] = dataset.ImagePositionPatient

medio/metadata/affine.py

@@ -33,7 +33,7 @@ def __new__(cls, affine=None, *, direction=None, spacing=None, origin=None):
  affine = cls.construct_affine(direction, spacing, origin)
  obj = np.asarray(affine).view(cls) # return array view of type Affine
  return obj
- 
+
  def __init__(self, affine=None, *, direction=None, spacing=None, origin=None):
  self.dim = self.shape[0] - 1
  if affine is None:
@@ -74,7 +74,8 @@ def spacing(self):
  def spacing(self, value):
  value = np.asarray(value)
  self._m_matrix = self._m_matrix @ np.diag(value / self._spacing)
- self._spacing = np.abs(value) # the spacing must be positive (or at least nonnegative)
+ # the spacing must be positive (or at least nonnegative)
+ self._spacing = np.abs(value)
 
  @property
  def direction(self):
@@ -124,4 +125,8 @@ def affine2direction(affine, spacing=None):
  def affine2comps(affine, spacing=None):
  if spacing is None:
  spacing = Affine.affine2spacing(affine)
- return Affine.affine2direction(affine, spacing), spacing, Affine.affine2origin(affine)
+ return (
+ Affine.affine2direction(affine, spacing),
+ spacing,
+ Affine.affine2origin(affine),
+ )

medio/metadata/convert_nib_itk.py

@@ -35,16 +35,16 @@
 
 # store compactly axis directions codes
 axes_inv = TwoWayDict()
-axes_inv['R'] = 'L'
-axes_inv['A'] = 'P'
-axes_inv['S'] = 'I'
+axes_inv["R"] = "L"
+axes_inv["A"] = "P"
+axes_inv["S"] = "I"
 
 
 def inv_axcodes(axcodes):
  """Inverse axes codes chars, for example: SPL -> IAR"""
  if axcodes is None:
  return None
- new_axcodes = ''
+ new_axcodes = ""
  for code in axcodes:
  new_axcodes += axes_inv[code]
  return new_axcodes

medio/metadata/dcm_uid.py

@@ -3,7 +3,7 @@
 from pydicom.uid import generate_uid
 
 # Given by Medical Connections (http:https://www.medicalconnections.co.uk/FreeUID.html)
-MEDIO_ROOT_UID = '1.2.826.0.1.3680043.10.513.'
+MEDIO_ROOT_UID = "1.2.826.0.1.3680043.10.513."
 
 
 generate_uid = partial(generate_uid, prefix=MEDIO_ROOT_UID)